Artículo: AMZ-B0GH6L5RMJ

Applied Artificial Intelligence and Probabilistic Machine Learning for Civil Engineers: Practical Applications, Uncertainty Quantification, Risk Analysis, and Infrastructure Decision-Making

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Paperback

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1.44 kg
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  • Applied Artificial Intelligence and Probabilistic Machine Learning for Civil Engineers presents a practical, engineering-oriented guide to integrating modern AI and machine learning techniques into civil and infrastructure engineering practice. The book bridges traditional civil engineering principles with data-driven intelligence, focusing on real-world applications rather than abstract theory.It introduces core concepts of machine learning, probabilistic modeling, and artificial intelligence, with special emphasis on uncertainty quantification, risk analysis, explainable AI (XAI), and causal inference. Readers learn how to apply AI methods to solve complex problems in geotechnical, structural, transportation, environmental, and infrastructure systems.Designed for students, researchers, and practicing engineers, the book provides intuitive explanations, practical workflows, and engineering-relevant case studies that demonstrate how AI can enhance decision-making, reliability, and performance in civil engineering projects. By combining interpretability, probabilistic reasoning, and engineering insight, this book equips readers with the tools needed to responsibly and effectively apply AI in modern civil engineering practice.
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